Document Type

Presentation

Publication Date

8-1-2014

Abstract

Many hydrological data systems provide Internet access to observational and processed data in various forms, from websites to web services. This data is generally described with basic metadata, such as units, names of measured variables, spatial coordinates, and so on. This metadata is largely suitable for further analysis or ingestion into hydrological models. However, when the data has been processed through many – potentially complex – steps, more information is required to give users details of implicit assumptions, inaccuracies, or uncertainties that may have been introduced. A common example of this within hydrology is the use of ratings tables to derive variables such as river discharge. Rating tables are generally developed through field observations using a wide range of methods and are subject to constant revision to adapt to changes in the physical world. Extracting details of rating conversions used in any of the hydrological data repositories found on the Internet is currently either not possible or quite difficult. A contributing factor to this is the lack of standard representations for rating tables and their related concepts. This paper describes work by members of the joint World Meteorology Organisation/Open Geospatial Consortium’s Hydrology Domain Working Group on development of an internationally harmonized information model to describe rating tables, called WaterML2.0 part 2. The paper covers the core aspects of the information model, its implementation within web services, and a visualization client for web-based analysis of rating tables. An international data exchange experiment has been setup to further test the information model in a number of exchange scenarios. The results will be used to refine and progress WaterML2.0 part 2 towards an open standard for data exchange. The standard will lead to increased transparency for data derived using ratings, resulting in improved integration with models and other analytical processes.

Comments

Session R01, Data and Information Models

 
 

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